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Abstract The design of the gas distribution for small-demand power plants located on remote islands is logistically challenging. The use of small-scale liquefied natural gas (LNG) vessels can be an option for these logistic problems. This paper aims to conduct a techno-economic analysis of using small-scale LNG vessels for gas distribution to the power plants that are spread across different islands. Route optimisation has been conducted using the capacitated vehicle routing problem method. The ship’s principal dimensions were determined using the aspect ratio from a linear regression of existing small-scale LNG vessels. As a case study, the gas demands for a gas power plant in eastern Indonesia were analysed into four distribution clusters. The results of the techno-economic analysis showed that the four distribution clusters have different characteristics regarding the LNG requirements, location characteristics and ship specifications. The capacity of small-scale LNG vessels feasible in terms of technical aspects varies from 2500, 5000, to > 10,000 m3 with variations in the ship speed depending on the location of the power plants. The amount of cargo requested and the shipping distance was affected to the cost of LNG transportation. The economic assessment proposes that the feasible investment by considering small-scale LNG cargo distribution, from the case study shows that with a ship capacity of 5000 m3 feasible margin rate is ≥ 3 USD/metric million British thermal units with an internal rate of return of 10% and estimated payback period is less than 15 years.

The development of liquefied natural gas (LNG) carrier ships is increasing rapidly along with the demand for alternative energy sources. This study aims to analyze the performance of an LNG-fueled propulsion system for a small-scale LNG carrier ship with a combination gas-electric steam turbine system (COGES). The performance of the propulsion system is analyzed based on the power output generation and the environmental effect of the system. The total power output was evaluated using thermodynamic analysis and the environmental impact was measured by carbon emissions using the life-cycle assessment approach. The analysis results show the COGES propulsion system potentially generates total power of 7600 kW at peak load. The desired ship operational speed of 12 knots can be achieved at 24% load of the total power output. The COGES propulsion system also indicates a low emission than other systems with a carbon emission is 0.149 kgCO2/kWh.

Autonomous ships are expected to extensively rely on perception sensors for situation awareness and safety during challenging operations, such as reactive collision avoidance. However, sensor noise is inevitable and its impact on end-to-end decision-making has not been addressed yet. This study aims to develop a methodology to enhance the robustness of decision-making for the reactive collision avoidance of autonomous ships against various perception sensor noise levels. A Gaussian-based noisy perception sensor is employed, where its noisy measurements and noise variance are incorporated into the decision-making as observations. A deep reinforcement learning agent is employed, which is trained in different noise variances. Robustness metrics that quantify the robustness of the agent’s decision-making are defined. A case study of a container ship using a LIDAR in a single static obstacle environment is investigated. Simulation results indicate sophisticated decision-making of the trained agent prioritising safety over efficiency when the noise variance is higher by conducting larger evasive manoeuvres. Sensitivity analysis indicates the criticality of the noise variance observation on the agent’s decision-making. Robustness is verified against noise variance up to 132% from its maximum trained value. Robustness is verified only up to 76% when the agent is trained without the noise variance observation with lack of its prior sophisticated decision-making. This study contributes towards the development of autonomous systems that can make safe and robust decisions under uncertainty.

Digital twins (DTs) are gradually employed in the maritime industry to represent the physical systems and generate datasets, among others. However, the trustworthiness of both the digital twins and datasets must be assured. This study aims at developing a framework to assure the trustworthiness of marine engines DTs based on first-principle models. This framework considers the phases of the DT development, progressivity, and trustworthiness assurance, the latter being based on three steps, namely validation, verification, and robustness. Subsequently, a methodology is applied to develop the DT of a marine engine for healthy conditions, which is extended to represent a wider operating envelope considering systematically identified anomalies. The results demonstrate that the developed DT trustworthiness is assured, as the validation step provided errors within ±3%, the verification step provided sound trade-offs, whereas the robustness assessment step confirmed acceptable uncertainty ratios. Subsequently, the DT is employed to generate datasets required for developing a data-driven model for anomaly diagnosis, which exhibits an accuracy of 98.8% for anomaly detection, 97.6% for anomaly identification, and 90.1–91.8% for anomaly isolation. This is the first study addressing the trustworthiness of DTs for marine engines, and as such advances concepts of the fourth industrial revolution to the shipping industry.

Various combinations of ship propulsion systems have been developed with low-carbon-emission technologies to meet regulations and policies related to climate change, one of which is the combined gas turbine and steam turbine integrated electric drive system (COGES), which is claimed to be a promising ship propulsion system for the future. The objective of this paper is to perform a techno-economic and environmental assessment of the COGES propulsion system applied to liquefied natural gas (LNG) carriers. A propulsion system design for a 7500 m3 LNG carrier was evaluated through the thermodynamics approach of the energy system. Subsequently, carbon emissions and environmental impact analyses were carried out through a life cycle assessment based on the power and fuel input of the system. Afterwards, a techno-economic analysis was carried out by considering the use of boil-off gas for fuel and additional income from carbon emission incentives. The proposed propulsion system design produces 1832 kilowatts of power for a service speed of 12 knots with the total efficiency of the system in the range of 30.1%. The results of the environmental evaluation resulted an overall environmental impact of 10.01 mPts/s. The results of the economic evaluation resulted in a positive net present value and a logical payback period for investment within 8 years of operation. The impact of this result shows that the COGES has a promising technological commercial application as an environmentally friendly propulsion system. Last, for the economy of the propulsion system, the COGES design has a positive net present value, an internal rate return in the range of 12–18%, and a payback period between 6 and 8 years, depending on the charter rate of the LNG carrier.

Methanol has been identified as a transition fuel for the decarbonisation of combustion-based industries, including automotive and maritime. This study aims to conduct a critical review of methanol combustion in compression ignition engines and analyse the reviewed studies’ results to quantify methanol use’s impact on engine performance and emissions characteristics. The diesel and diesel–methanol operation of these engines are comparatively assessed, demonstrating the trade-offs between the methanol fraction, the key engine performance parameters, including brake thermal efficiency, peak in-cylinder pressure, heat release rate, and temperature, as well as the carbon dioxide, carbon monoxide, nitrogen oxides, and particulate matter emissions. The types of the reviewed engines considering the main two combustion methods, namely premixed and diffusion combustion, are discussed. Research gaps are identified, and recommendations for future research directions to address existing challenges for the wider use of methanol as a marine fuel are provided. This comprehensive review provides insights supporting methanol engine operation, and it is expected to lead to further studies towards more efficient use of methanol-fueled marine engines.

Recently, the marine industry has been under a paradigm shift toward adopting increased automation, and initiatives to enable the autonomous operations of ships are ongoing. In these cases, power plants require advanced monitoring techniques not only for the performance parameters but also to assess the health state of their critical components. In this respect, this study aims to develop a monitoring functionality for power plants that captures the performance metrics while considering the overall system and its components' reliability. A hybrid power plant of a pilot boat is considered a case study. A rule-based energy management strategy is adopted, which makes the decisions on the power distribution to the investigated power plant components. Additionally, a dynamic Bayesian network is developed to capture the temporal behavior of the system's/components' reliability accounting for the power plant's operating profile. Results demonstrate that the selected hybrid power plant monitoring capabilities are enhanced by providing the power plant performance along with the estimation of the system's health state. Furthermore, these extended monitoring capabilities can provide the essential metrics to facilitate decisionmaking, enabling the autonomous operation of the power plant.

Several countries heavily depend on their domestic ferries, the decarbonisation of which are required following the prevailing and forthcoming international and national carbon reduction targets. This study aims to conduct an environmental-economic analysis to identify the impact of three decarbonisation measures, specifically, hybridisation, liquified natural gas (LNG) and methanol use, for two ferries of different size of a developing country fleet. The study is based on several methodological steps including the selection of key performance indicators (KPIs), the pre-processing of acquired data to identify representative operating profiles, the environmental and economic KPIs calculation, as well as the comparative appraisal of the investigated measures. The required investments for decarbonising the whole domestic fleet of a case country are subsequently estimated and discussed. All the three investigated measures have the potential to reduce CO2 emissions, however, not beyond the IMO 2030 carbon emissions reduction target. This study provides insights to the involved stakeholders for supporting their decisions pertinent to the domestic ferries sector decarbonisation.

In-cylinder pressure is a key parameter for assessing marine engines health; therefore, its measurement or prediction is paramount for these engines’ diagnosis. Thermodynamic models are typically employed for predicting the in-cylinder pressure, which, however, face challenges pertinent to their calibration and computational time requirements. Recent advances in the field of machine learning have leveraged the development of data-driven models. This study aims to compare two approaches for input features and six regression techniques to select the most effective combination for developing data-driven models to predict the in-cylinder pressure of marine four-stroke engines. Two approaches with different input and output features are initially compared. The first employs regression to directly predict the in-cylinder pressure signal, whereas the second predicts the harmonics coefficients by regression and subsequently estimates the in-cylinder pressure by using a Fourier series function. Typical regression techniques, including linear, elastic, and polynomial regression, support vector machines (SVM), decision trees (DT), and artificial neural networks (ANN), are employed to develop data-driven models based on the second approach. The required datasets for training and testing are derived by using a physical digital twin for the investigated marine engine, which is calibrated against the shop trials and acquired shipboard measurements. The accuracy of the data-driven models are estimated based on the root mean square error considering the testing datasets. For the data-driven model based on the second approach and the ANN regression, a sensitivity study is carried out considering the training datasets and the harmonics number to derive recommendations for these parameters’ values. The results demonstrate that the second approach provides higher accuracy, whereas the ANN regression is the most effective technique for developing data-driven models to estimate the in-cylinder pressure, as the exhibited root mean square error is retained within ±0.2 bar for the ANN trained with 20 samples. This study supports the development and use of data-driven models for marine engines health diagnosis.

ABSTRACTThis project aims at developing an efficient simulation environment for the vessel navigation system. The design of the overall navigation system is described along with its application for the case study of an autonomous vessel. The UNITY and Robot Operating System were utilised as the virtual environment and the main control framework, respectively. By treating the autonomous vessel as a single robot, each part of the system was formulated to enhance the efficiency and visualisation in the development progresses for autonomous system. The virtual environment using UNITY overwhelms the space-time constraints in the testing stage. The navigation system combined with conventional navigation algorithms and a computer vision algorithm were implemented in the Robot Operating System. Hence, the navigation system was enhanced by an assistant object detection algorithm to be more active on fusing environment information. The excellence of the proposed object detection model was demonstrated with reliable performance with 94% mean Average Precision, which renders the model exhibiting visual sensibility in navigation. Overall, it is believed that this study can contribute to offering some insights into developing autonomous marine vessels.

Pursuing net-zero emission operations in the shipping industry are quintessential for this sector to mitigate the environmental impact caused by hydrocarbon fuel combustion. Significant contributions to this are expected from the substitution of conventional marine fuels by alternative, emission-free fuels with lower emission footprints. This study aims to conduct a comprehensive literature review for delineating the main characteristics of the considered alternative fuels, specifically focusing on hydrogen, methanol, and ammonia, which have recently attracted attention from both industry and academia. This study comparatively assesses the potential of using these fuels in marine engines, and their subsequent performance characteristics as well as the associated environmental benefits. In addition, the required storage conditions, space, as well as the associated costs, are reviewed. Special attention is given to the safety characteristics and requirements for each alternative fuel. The results of this study demonstrate that the environmental benefits gained from alternative fuel use are pronounced only when renewable energy is considerably exploited for their production, whereas the feasibility of each fuel depends on the vessel type used and pertinent storage constraints. Hydrogen, ammonia, and methanol are considered best-fit solutions for small scale shipping, requiring minimal on-board storage. In addition, the need for comparative assessments between diesel and alternative fuels is highlighted and sheds light on marine engines’ operational characteristics. Moreover, using combinations of alternative and diesel fuels is identified as a direction towards decarbonisation of the maritime sector; intensifying the need for optimisation studies on marine engine design and operation. This study concludes with recommendations for future research directions, thus contributing to fuel research concepts that can facilitate the shipboard use of alternative fuels.

This study aims to investigate the impact of the High Pressure Selective Catalytic Reduction system (SCR-HP) on a large marine two-stroke engine performance parameters by employing thermodynamic modelling. A coupled model of the zero-dimensional type is extended to incorporate the modelling of the SCR-HP components and the Control Bypass Valve (CBV) block. This model is employed to simulate several scenarios representing the engine operation at both healthy and degraded conditions considering the compressor fouling and the SCR reactor clogging. The derived results are analysed to quantify the impact of the SCR-HP on the investigated engine performance. The SCR system pressure drop and the cylinder bypass valve flow cause an increase of the engine Specific Fuel Oil Consumption (SFOC) in the range 0.3–2.77 g/kWh. The thermal inertia of the SCR-HP is mainly attributed to the SCR reactor, which causes a delayed turbocharger response. These effects are more pronounced at low engine loads. This study supports the better understanding of the operating characteristics of marine two-stroke diesel engines equipped with the SCR-HP and quantification of the impact of the components degradation on the engine performance.

The autonomous ships’ introduction is associated with a number of challenges including the lack of appropriate risk acceptance criteria to support the risk assessment process during the initial design phases. This study aims to develop a rational methodology for selecting appropriate risk matrix ratings, which are required to perform the risk assessment of autonomous and conventional ships at an early design stage. This methodology consists of four phases and employs the individual and societal risk acceptance criteria to determine the risk matrix ratings for the groups of people exposed to risks. During the first and second phase, the required input parameters for the risk matrix ratings based on the individual risk and societal risk are calculated, respectively. During the third phase, the risk matrix ratings are defined using input from the first and second phases. During the fourth phase, the equivalence between the different types of consequences is specified. The methodology is applied for the case study of a crewless inland waterways ship to assess her typical operation within north-European mainland. The results demonstrate that the inclusion of societal risk resulted in more stringent risk matrix ratings compared to the ones employed in previous studies. Moreover, the adequacy of the proposed methodology and its effectiveness to provide risk acceptance criteria aligned with societal and individual risk acceptance criteria as well as its applicability to conventional ships are discussed.

The shipping sector decarbonisation has attracted great attention due to the sector contribution to worldwide carbon emissions. This study aims at investigating the techno-economic–environmental performance of different ship power plants to identify sustainable solutions for a case study cargo ship. Four scenarios, considering conventional and hybrid power plants, the latter with installed batteries, both using marine gas oil and ammonia fuels, are analysed to estimate the pertinent lifetime key performance indicators characterising their economic and environmental performance. Additionally, taxation schemes of varying extent are considered, and a sensitivity analysis is carried out on the most uncertain input parameters, namely, fuel prices and capital cost. This study results demonstrate that the hybrid plant using ammonia exhibits the lowest environmental footprint associated with 66% carbon emission reduction, whilst increasing the lifetime cost by 40%. Taxation schemes close to 340 EUR per CO2 tonne are required to render it economically viable whilst meeting the IMO targets for 2050 on CO2 emissions reduction. The sensitivity analysis reveals that the economic parameters is highly sensitive to fuel price and the capital expenditure.

Although the exhaust gas recirculation (EGR) technology has been proven effective to decrease the marine engine’s nitrogen oxides (NOx) emissions, it is associated with a considerable fuel consumption increase and challenges to the engine–turbocharger matching. This study aims to parametrically optimise the EGR and turbocharging system settings of a large marine two-stroke engine with the objective of obtaining the highest engine efficiency whilst ensuring compliance with the prevailing NOx emissions limits. Two typical configurations of the investigated engine (baseline and alternative) are modelled in the GT-SUITE software. Parametric simulations are performed with EGR rates up to 40% along with cylinder bypass rates up to 50%, and the simulation results are analysed to quantify the impact of the engine operation with EGR on the performance and NOx emissions parameters. For the baseline engine configuration, the EGR rate increase considerably deteriorates the brake specific fuel consumption (BSFC), which is attenuated by opening the cylinder bypass valve. The optimal combinations of the EGR and cylinder bypass rates for each operating point are identified for both configurations. Following the comparative assessment between the two engine configurations, recommendations for the engine operating modes are proposed, leading to BSFC improvement in the region of 0.7 to 2.9 g/kWh. This study provides insights for the operational settings optimisation of two-stroke engines equipped with EGR systems, contributing towards the reduction of the associated environmental carbon footprint.

Recently, the shipping industry has been under increasing pressure to improve its environmental impact with a target of a 50% reduction in greenhouse gas emissions by 2050, compared to the 2008 levels. For this reason, great attention has been placed on alternative zero-carbon fuels, specifically ammonia, which is considered a promising solution for shipping decarbonisation. In this respect, a novel ammonia-powered fuel-cell configuration is proposed as an energy-efficient power generation configuration with excellent environmental performance. However, there are safety and reliability concerns of the proposed ammonia-powered system that need to be addressed prior to its wider acceptance by the maritime community. Therefore, this is the first attempt to holistically examine the safety, operability, and reliability of an ammonia fuel-cell-powered ship, while considering the bunkering and fuel specifications. The proposed methodology includes the novel combination of a systematic preliminary hazard identification process with a functional and model-based approach for simulating the impact of various hazards. Furthermore, the critical faults and functional failures of the proposed system are identified and ranked according to their importance. This work can be beneficial for both shipowners and policymakers by introducing technical innovation and for supporting the future regulatory framework.

Stringent environmental regulations and efforts to improve the shipping operations sustainability have resulted in designing and employing more complex configurations for the ship power plants systems and the implementation of digitalised functionalities. Due to these systems complexity, critical situations arising from the components and subsystem failures, which may lead to accidents, require timely detection and mitigation. This study aims at enhancing the safety of ship complex systems and their operation by developing the concept of an integrated monitoring safety system that employs existing safety models and data fusion from shipboard sensors. Detailed Fault Trees that model the blackout top event, representing the sailing modes of a cruise ship and the operating modes of its plant, are employed. Shipboard sensors’ measurements acquired by the cruise ship alarm and monitoring system are integrated with these Fault Trees to account for the acquired shipboard information on the investigated power plant configuration and its components operating conditions, thus, facilitating the estimation of the blackout probability time variation as well as the dynamic criticality assessment of the power plant components. The proposed concept is verified by using a virtual simulation environment developed in Matlab/Simulink. This study supports the dynamic assessment of the ship power plants and therefore benefits the decision-making for enhancing the plant safety during operations.

Diesel–Electric Propulsion (DEP) has been widely used for the propulsion of various ship types including cruise ships. Considering the potential consequences of blackouts, especially on cruise ships, it is essential to design and operate the ships’ power plants for avoiding and preventing such events. This study aims at implementing a comprehensive safety analysis for a cruise ship Diesel–Electric Propulsion (DEP) plant focusing on blackout events. The Combinatorial Approach to Safety Analysis (CASA) method is used to develop Fault Trees considering the blackout as the top event, and subsequently estimate the blackout frequency as well as implement importance analysis. The derived results demonstrate that the overall blackout frequency is close to corresponding values reported in the pertinent literature as well as estimations based on available accident investigations. This study deduces that the blackout frequency depends on the number of operating Diesel Generator (DG) sets, the DG set’s loading profile, the amount of electrical load that can be tripped during overload conditions and the plant operation phase. In addition, failures of the engine auxiliary systems and the fast-electrical load reduction functions, as well as the power generation control components, are identified as important. This study demonstrates the applicability of the CASA method to complex marine systems and reveals the parameters influencing the investigated system blackout frequency, thus providing better insights for these systems’ safety analysis and enhancement.

In April 2018, the International Maritime Organisation adopted an ambitious plan to contribute to the global efforts to reduce the Greenhouse Gas emissions, as set by the Paris Agreement, by targeting a 50% reduction in shipping’s Green House Gas emissions by 2050, benchmarked to 2008 levels. To meet these challenging goals, the maritime industry must introduce environmentally friendly fuels with negligible, or low SOX, NOX and CO2 emissions. Ammonia use in maritime applications is considered promising, due to its high energy density, low flammability, easy storage and low production cost. Moreover, ammonia can be used as fuel in a variety of propulsors such as fuel cells and can be produced from renewable sources. As a result, ammonia can be used as a versatile marine fuel, exploiting the existing infrastructure, and having zero SOX and CO2 emissions. However, there are several challenges to overcome for ammonia to become a compelling fuel towards the decarbonisation of shipping. Such factors include the selection of the appropriate ammonia-fuelled power generator, the selection of the appropriate system safety assessment tool, and mitigating measures to address the hazards of ammonia. This paper discusses the state-of-the-art of ammonia fuelled fuel cells for marine applications and presents their potential, and challenges.

In this study a coupled thermodynamics and crankshaft dynamics model of a large two-stroke diesel engine was utilised, to map the relationship of the engine Instantaneous Crankshaft Torque (ICT) with the following frequently occurring malfunctioning conditions: (a) change in Start of Injection (SOI), (b) change in Rate of Heat Release (RHR), (c) change in scavenge air pressure, and (d) blowby. This was performed using frequency analysis on the engine ICT, which was obtained through a series of parametric runs of the coupled engine model, under the various malfunctioning and healthy operating conditions. This process demonstrated that engine ICT can be successfully utilised to identify the distinct effects of malfunctions (c) or (d), as they occur individually in any cylinder. Furthermore by using the same process, malfunctions (a) and (b) can be identified as they occur individually for any cylinder, however there is no distinct effect on the engine ICT among these malfunctions, since their effect on the in-cylinder pressure is similar. As a result, this study demonstrates the usefulness of the engine ICT as a non-intrusive diagnostic measurement, as well as the benefits of malfunctioning conditions mapping, which allows for quick and less resource intensive identification of engine malfunctions.

Recent regulatory requirements for shipping emissions control have led to the adoption of Liquefied Natural Gas (LNG) as a marine fuel and the design of LNG-fuelled vessels. Considering the potential safety implications due to system failure/unavailability, this study aims at the safety analysis of a low-pressure LNG fuel feeding system using a novel model-based methodology. The proposed methodology is based on the functional system modelling, leading to the failure diagrams development, and combines the use of Failure Modes, Effects, and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA), which are performed in MADe™ and PTC Windchill software environments. The FMECA results are employed to identify the investigated system critical components and failures as well as specifying the top events for the subsequently performed FTA, which evaluates the top events failure rates. The system critical components identification leads to the system design modification targeting reduced safety metrics. This study results demonstrate that the evaporator, pressure build-up unit, sensors, and cryogenic valve assemblies are the most critical components of the investigated system, whilst the enhanced system design exhibits a failure rate reduced by 69% in comparison to the baseline system. This study reveals the advantages of the developed methodology along with some limitations of the employed tools and contributes to the quantitative safety analysis and design of ship complex systems.

This Special Issue presents a collection of articles addressing the contemporary challenges in the areas of the ship energy systems modelling and optimisation [...]

Dual fuel engines constitute a viable solution for enhancing the environmental sustainability of the shipping operations. Although these engines comply with the Tier III NOx emissions regulations when operating at the gas mode, additional measures are required to ensure such compliance at the diesel mode. Hence, this study aimed to optimise the settings of a marine four-stroke dual fuel (DF) engine equipped with exhaust gas recirculation (EGR) and air bypass (ABP) systems by employing simulation and optimisation techniques, so that the engine when operating at the diesel mode complies with the ‘Tier III’ requirements. A previous version of the engine thermodynamic model was extended to accommodate the EGR and ABP systems modelling. Subsequently, a combination of optimisation techniques including multiobjective genetic algorithms (MOGA) and design of experiments (DoE) parametric runs was employed to identify both the engine and the EGR/ABP systems settings with the objective to minimise the engine brake specific fuel consumption and reduce the NOx emissions below the Tier III limit. The derived simulation results were employed to analyse the EGR system involved interactions and their effects on the engine performance and emissions trade-offs. A sensitivity analysis was performed to reveal the interactions between considered engine settings and quantify their impact on the engine performance parameters. The derived results indicate that EGR rates up to 35% are required, so that the investigated engine with EGR and ABP systems, when operating at the diesel mode, achieves compliance with the ‘Tier III’ NOx emissions, whereas the associated engine brake specific fuel consumption penalty is up to 8.7%. This study demonstrates that the combination of EGR and ABP systems can constitute a functional solution for achieving compliance with the stringent regulatory requirements and provides a better understating of the underlined phenomena and interactions of the engine subsystems parameters variations for the investigated engine equipped with EGR and ABP systems.

Fully electric ships have been widely developed, investigated and evaluated by the maritime industry as a potential solution to respond to the emissions control required according to the International Maritime Organization (IMO). This study aims at presenting a novel approach to evaluate the safety level of a battery-powered high speed catamaran. Following the Formal Safety Assessment procedure, the risk assessment of the considered ship was conducted leading to the identification of the involved hazards along with the estimation of their frequency and consequences thus allowing for the identification of the most severe hazards. Fault tree analysis is carried out for and the identified top events followed by an event tree analysis to estimate the risk and safety level of the vessel. Furthermore, a cost-benefit assessment is conducted to evaluate the financial impact of selected risk control options. The derived results indicate that the application of battery power systems for high speed ferries exhibits low and acceptable accident frequencies. It is also supported the current regulation to carry out mandatory risk assessment for battery-powered ships.

Both spark ignition (SI) natural gas engines and compression ignition (CI) dual fuel (DF) engines suffer from knocking when the unburnt mixture ignites spontaneously prior to the flame front arrival. In this study, a parametric investigation is performed on the knocking performance of these two engine types by using the GT-Power software. An SI natural gas engine and a DF engine are modelled by employing a two-zone zero-dimensional combustion model, which uses Wiebe function to determine the combustion rate and provides adequate prediction of the unburnt zone temperature, which is crucial for the knocking prediction. The developed models are validated against experimentally measured parameters and are subsequently used for performing parametric investigations. The derived results are analysed to quantify the effect of the compression ratio, air-fuel equivalence ratio and ignition timing on both engines as well as the effect of pilot fuel energy proportion on the DF engine. The results demonstrate that the compression ratio of the investigated SI and DF engines must be limited to 11 and 16.5, respectively, for avoiding knocking occurrence. The ignition timing for the SI and the DF engines must be controlled after −38°CA and 3°CA, respectively. A higher pilot fuel energy proportion between 5% and 15% results in increasing the knocking tendency and intensity for the DF Engine at high loads. This study results in better insights on the impacts of the investigated engine design and operating settings for natural gas (NG)-fuelled engines, thus it can provide useful support for obtaining the optimal settings targeting a desired combustion behaviour and engine performance while attenuating the knocking tendency.

Cyber-Physical Systems (CPSs) represent a systems category developed and promoted in the maritime industry to automate functions and system operations. In this study, a novel Combinatorial Approach for Safety Analysis is presented, which addresses the traditional safety methods’ limitations by integrating System Theoretic Process Analysis (STPA), Events Sequence Identification (ETI) and Fault Tree Analysis (FTA). The developed method results in the development of a detailed Fault Tree that captures the effects of both the physical components/subsystems and the software functions’ failures. The quantitative step of the method employs the components’ failure rates to calculate the top event failure rate along with importance metrics for identifying the most critical components/functions. This method is implemented for an exhaust gas open loop scrubber system safety analysis to estimate its failure rate and identify critical failures considering the baseline system configuration as well as various alternatives with advanced functions for monitoring and diagnostics. The results demonstrate that configurations with SOx sensor continuous monitoring or scrubber unit failure diagnosis/prognosis lead to significantly lower failure rate. Based on the analysis results, the advantages/disadvantages of the novel method are also discussed. This study also provides insights for better safety analysis of the CPSs.

The crankshaft dynamics model is of vital importance to a multitude of aspects on engine diagnostics; however, systematic investigations of such models performance (especially for large two-stroke diesel engines that are widely used in the power generation and shipping industries) have not been reported in the literature. This study aims to cover this gap by systematically investigating the parameters that affect the performance of a two-stroke diesel engine crankshaft dynamics model, such as the numerical scheme as well as the engine components inertia and friction. Specifically, the following alternatives are analysed: (a) two optimal performing numerical schemes, in particular, a stiff ordinary differential equations (ODE) solver and a fast solver based on a piecewise Linear Time-Invariant (LTI) scheme method, (b) the linear and the non-linear inertia-speed approaches, and (c) three engine friction submodels of varying complexity. All the potential combinations of the alternatives are investigated, and the crankshaft dynamics model performance is evaluated by employing Key Performance Indicators (KPIs), which consider the results accuracy compared to the measured data, the computational time, and the energy balance error. The results demonstrate that the best performing combination includes the stiff ODE solver, the constant inertia-speed approach and the most simplistic engine friction submodel. However, the LTI numerical scheme is recommended for applications that require fast response due to the significant savings in computational time with an acceptable compromise in the model results accuracy.

This study aims at developing an integrated model that combines detailed engine thermodynamic modelling and the control system functional modelling paving the way towards the development of high-fidelity digital twins. To sufficiently represent the combustion process, a multi-Wiebe function approach was employed, whereas a database for storing the combustion model parameters was developed. The developed model was employed for the systematic investigation of a marine four-stroke dual fuel engine response during demanding transient operation with mode switching and load changes. The derived results were analysed to identify the critical engine components and their effect on the engine operational limitations. The results demonstrate that the developed model can sufficiently represent the engine and its subsystems/components behaviour and effectively capture the engine control system’s functionality. The appropriate turbocharger matching along with the sufficient design of the exhaust gas waste gate valve and fuel control systems are crucial for ensuring the smooth engine operation of dual fuel engines.

The Energy Efficiency Design Index (EEDI) was introduced as a regulatory tool employed at the ship design phase to reduce the carbon dioxide (CO2) emissions and increase the vessel’s operational efficiency. Although it stimulated the greening of the shipping operations, its effectiveness is considerably criticised from various shipping industry stakeholders. The aim of this study is to investigate the EEDI effectiveness on accurately representing the environmental performance of the next-generation ships power plants for two representative ship types, in specific, an ocean-going tanker and a cruise ship. The performance of the optimal power plant solutions identified in previous studies is analysed according to the existing EEDI regulatory framework and compared with the lifetime CO2 emissions estimated based on an actual operating profile for each ship. The results indicate that the EEDI underestimates the effect of technologies for reducing carbon emissions in all the investigated cases. In this respect, it is concluded that EEDI is classified as a conservative metric, which however can be used as an approximation to compare alternative solutions early in the design phase.

In this article, the operation of a large two-stroke marine diesel engine including various cases with turbocharger cut-out was thoroughly investigated by using a modular zero-dimensional engine model built in MATLAB/Simulink environment. The model was developed by using as a basis an in-house modular mean value engine model, in which the existing cylinder block was replaced by a more detailed one that is capable of representing the scavenging ports-cylinder-exhaust valve processes. Simulation of the engine operation at steady state conditions was performed and the derived engine performance parameters were compared with the respective values obtained by the engine shop trials. The investigation of engine operation under turbocharger cut-out conditions in the region from 10% to 50% load was carried out and the influence of turbocharger cut-out on engine performance including the in-cylinder parameters was comprehensively studied. The recommended schedule for the combination of the turbocharger cut-out and blower activation was discussed for the engine operation under part load conditions. Finally, the influence of engine operating strategies on the annual fuel savings, CO2 emissions reduction and blower operating hours for a Panamax container ship operating at slow steaming conditions is presented and discussed.